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Using Human Movement Data to Identify Potential Areas of Zika Transmission: Case Study of the Largest Zika Cluster in Singapore

Author

Listed:
  • Jayanthi Rajarethinam

    (Environmental Health Institute, National Environment Agency, 11 Biopolis Way, #06-05-08, Singapore 138667, Singapore)

  • Janet Ong

    (Environmental Health Institute, National Environment Agency, 11 Biopolis Way, #06-05-08, Singapore 138667, Singapore)

  • Shi-Hui Lim

    (Starhub Limited, 67 Ubi Avenue 1, #05-01 StarHub Green, Singapore 408942, Singapore)

  • Yu-Heng Tay

    (Starhub Limited, 67 Ubi Avenue 1, #05-01 StarHub Green, Singapore 408942, Singapore)

  • Wacha Bounliphone

    (Environmental Health Institute, National Environment Agency, 11 Biopolis Way, #06-05-08, Singapore 138667, Singapore)

  • Chee-Seng Chong

    (Environmental Health Institute, National Environment Agency, 11 Biopolis Way, #06-05-08, Singapore 138667, Singapore)

  • Grace Yap

    (Environmental Public Health Operations, National Environment Agency, 40 Scotts Road, #13-00 Environment Building, Singapore 228231, Singapore)

  • Lee-Ching Ng

    (Environmental Health Institute, National Environment Agency, 11 Biopolis Way, #06-05-08, Singapore 138667, Singapore
    School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore 637551, Singapore)

Abstract

Singapore experienced its first Zika virus (ZIKV) cluster in August 2016. To understand the implication of human movement on disease spread, a retrospective study was conducted using aggregated and anonymized mobile phone data to examine movement from the cluster to identify areas of possible transmission. An origin–destination model was developed based on the movement of three groups of individuals: (i) construction workers, (ii) residents and (iii) visitors out of the cluster locality to other parts of the island. The odds ratio of ZIKV cases in a hexagon visited by an individual from the cluster, independent of the group of individuals, is 3.20 (95% CI: 2.65–3.87, p -value < 0.05), reflecting a higher count of ZIKV cases when there is a movement into a hexagon from the cluster locality. A comparison of independent ROC curves tested the statistical significance of the difference between the areas under the curves of the three groups of individuals. Visitors (difference in AUC = 0.119) and residents (difference in AUC = 0.124) have a significantly larger difference in area under the curve compared to the construction workers ( p -value < 0.05). This study supports the proof of concept of using mobile phone data to approximate population movement, thus identifying areas at risk of disease transmission.

Suggested Citation

  • Jayanthi Rajarethinam & Janet Ong & Shi-Hui Lim & Yu-Heng Tay & Wacha Bounliphone & Chee-Seng Chong & Grace Yap & Lee-Ching Ng, 2019. "Using Human Movement Data to Identify Potential Areas of Zika Transmission: Case Study of the Largest Zika Cluster in Singapore," IJERPH, MDPI, vol. 16(5), pages 1-13, March.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:5:p:808-:d:211164
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    References listed on IDEAS

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    1. Bruce Y Lee & Jorge A Alfaro-Murillo & Alyssa S Parpia & Lindsey Asti & Patrick T Wedlock & Peter J Hotez & Alison P Galvani, 2017. "The potential economic burden of Zika in the continental United States," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 11(4), pages 1-20, April.
    2. Neil M. Ferguson & Derek A.T. Cummings & Simon Cauchemez & Christophe Fraser & Steven Riley & Aronrag Meeyai & Sopon Iamsirithaworn & Donald S. Burke, 2005. "Strategies for containing an emerging influenza pandemic in Southeast Asia," Nature, Nature, vol. 437(7056), pages 209-214, September.
    3. Stephen Eubank & Hasan Guclu & V. S. Anil Kumar & Madhav V. Marathe & Aravind Srinivasan & Zoltán Toroczkai & Nan Wang, 2004. "Modelling disease outbreaks in realistic urban social networks," Nature, Nature, vol. 429(6988), pages 180-184, May.
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    Cited by:

    1. Yuqi Zhang & Hongyan Ren & Runhe Shi, 2022. "Influences of Differentiated Residence and Workplace Location on the Identification of Spatiotemporal Patterns of Dengue Epidemics: A Case Study in Guangzhou, China," IJERPH, MDPI, vol. 19(20), pages 1-19, October.
    2. Shuli Zhou & Suhong Zhou & Lin Liu & Meng Zhang & Min Kang & Jianpeng Xiao & Tie Song, 2019. "Examining the Effect of the Environment and Commuting Flow from/to Epidemic Areas on the Spread of Dengue Fever," IJERPH, MDPI, vol. 16(24), pages 1-13, December.

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